Case Study: Grand Rapids achieves real-time sewer construction QA with VAPAR AI

Grand Rapids accelerates sewer QA with VAPAR, flagging 100 defects early

The city of Grand Rapids faced a challenge in its sewer construction quality assurance process. After new pipes were installed, traditional manual reviews of CCTV footage delayed defect identification for days or weeks. This lag often meant issues like joint offsets or debris were discovered only after construction crews had left the site, leading to costly rework, contractor remobilization, and community disruption. The utility needed a faster way to identify defects while crews were still present to enable immediate correction.

Grand Rapids implemented VAPAR's AI-powered platform to automatically analyze post-installation CCTV footage. The VAPAR AI solution provided structured, inspection-ready outputs within hours, clearly flagging and timestamping defects. This accelerated feedback loop allowed the city to identify and resolve issues while construction crews were still mobilized, avoiding delayed discovery. The results included a significant reduction in rework costs and community disruption, with over 30,000 linear feet assessed and 100 defects identified early in the construction phase.

Grand Rapids